755 research outputs found

    Pulmonary versus aortic pressure behavior of a bovine pericardial valve

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    Background: The Carpentier Edwards Perimount Magna Ease aortic valvular prosthesis (Edwards Lifesciences, Irvine, Calif) has been among the most frequently and successfully used tissue prosthetic cardiac valves. Furthermore, this prosthesis has been used off-label in the pulmonary position. Until now, there has been a paucity of data regarding the functioning of tissue prosthetic valves under pulmonary conditions. Methods: Using a pulse duplicator, hydrodynamic characteristics of a 21-mm and 25-mm Magna Ease valve were evaluated. Among parameters evaluated were leakage orifice area, closing time (ie, time required to close), and leakage duration. This procedure was performed under different pulmonic pressure conditions (15/5 mm Hg, 28/11 mm Hg, 73/32 mm Hg) and normal aortic pressure (120/80 mm Hg) as a reference. Moving images were obtained using a Phantom MIRO M320S high-speed camera (Vision Research Inc, Wayne, NJ) at 600 frames per second and used to analyze valve area in closed position. Results: Under normal pulmonic conditions (28/11 mm Hg) the leakage orifice area was 0.020 ± 0.012 mm2 for the 21-mm valve and 0.054 ± 0.041 mm2 for the 25-mm valve (P = .03). Hydrodynamic characteristics of the valves differed between pulmonary and aortic testing condition. Valve closing volumes were significantly lower under pulmonary hypotension and normal pulmonary conditions than under normal aortic conditions (P < .05). Conclusions: Under normal pulmonary pressure conditions, the hydrodynamic characteristics of Magna Ease valves are significantly different compared with aortic conditions. Further research is needed to determine whether these results are associated with prosthetic valve failure

    Virtual Machining: Capabilities and Challenges of Process Simulations in the Aerospace Industry

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    AbstractMilling processes for the manufacturing of parts for aerospace applications can be influenced by various effects. When machining structural parts with high material removal rates, the stiffness of the machine tool can be a limiting factor because chatter vibrations. Additionally, vibrations of thin-walled structures, e. g., the blades of impellers or turbines, can lead to chatter vibrations and surface location errors. Thermo-mechanical deformations are another cause for violations of given shape tolerances. Geometric physically-based process simulations can be used to analyze milling processes with regard to these effects in order to optimize the process parameters. In this paper, an overview of several applications of a geometric physically-based simulation system for analyzing different effects during milling processes is presented. Depending on the relevant effects, process forces, the dynamic behaviour of the tool-spindle-machine system, vibrations of workpieces and fixture systems, as well as thermo-mechanical deformations are calculated

    Quantitative projections of a quality measure: Performance of a complex task

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    AbstractComplex data series that arise during interaction between humans (operators) and advanced technology in a controlled and realistic setting have been explored. The purpose is to obtain quantitative measures that reflect quality in task performance: on a ship simulator, nine crews have solved the same exercise, and detailed maneuvering histories have been logged. There are many degrees of freedom, some of them connected to the fact that the vessels may be freely moved in any direction. To compare maneuvering histories, several measures were used: the time needed to reach the position of operation, the integrated angle between the hull direction and the direction of motion, and the extent of movement when the vessel is to be manually kept in a fixed position. These measures are expected to reflect quality in performance. We have also obtained expert quality evaluations of the crews. The quantitative measures and the expert evaluations, taken together, allow a ranking of crew performance. However, except for time and integrated angle, there is no correlation between the individual measures. This may indicate that complex situations with social and man–machine interactions need complex measures of quality in task performance. In general terms, we have established a context-dependent and flexible framework with quantitative measures in contact with a social-science concept that is hard to define. This approach may be useful for other (qualitative) concepts in social science that contain important information on the society

    Diabetes, Glycemic Control, and New-Onset Heart Failure in Patients With Stable Coronary Artery Disease: Data from the Heart and Soul Study

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    OBJECTIVE Diabetes is a predictor of both coronary artery disease (CAD) and heart failure. It is unknown to what extent the association between diabetes and heart failure is influenced by other risk factors for heart failure. RESEARCH DESIGN AND METHODS We evaluated the association of diabetes and A1C with incident heart failure in outpatients with stable CAD and no history of heart failure (average follow-up 4.1 years). RESULTS Of 839 participants, 200 had diabetes (23.8%). Compared with patients who did not have diabetes, those with diabetes had an increased risk of heart failure (hazard ratio [HR] 2.17 [95% CI 1.37-3.44]). Adjustment for risk factors for CAD (age, sex, race, smoking, physical inactivity, obesity, blood pressure, and LDL cholesterol), interim myocardial infarction, and myocardial ischemia did not alter the strength of the association between diabetes and heart failure. After inclusion also of other risk factors for heart failure (left ventricular ejection fraction, diastolic dysfunction, and C-reactive protein) and medication use, diabetes remained an independent predictor of heart failure (HR 3.34 [95% CI 1.65-6.76]; P = 0.001). Each 1% increase in A1C concentration was associated with a 36% increased HR of heart failure hospitalization (HR 1.36 [95% CI 1.17-1.58]). CONCLUSIONS In patients with stable CAD who are free from heart failure at baseline, diabetes and glycemic control are independent risk factors for new-onset heart failure. The mechanisms by which diabetes and hyperglycemia lead to heart failure deserve further study, as the association is independent of baseline functional assessment of ischemia, systolic and diastolic function, and interim myocardial infarction
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